We aim to develop an epistemology based on dialogue among different disciplines and a complex system perspective that avoids the temptations of reductionism.
Social sciences must deal with phenomena that have no counterpart in the physical or even the biological world, and so the temptation to carry over fundamental concepts and methods from physics and evolutionary biology, for example, to the social domain, must be regarded with a healthy dose of skepticism.
We seek to construct methods that go well beyond the current innovation and sustainability literature, by developing an approach that links these two themes from a complex systems perspective, which we consider better suited to grasp physical and social phenomena. These methods involve new interpretations of what theory is, and how theory can enter into productive, on-going dialogue with models and case studies.
The social phenomena we study have many implications, including in particular ontological uncertainty, inherent limits of predictability, and highly nonstationary process dynamics that generate perpetual novelty. These elements render unusable the very bases of physics’ remarkable successes: Galileo’s experimental strategy for discovering fundamental system invariants; Newton’s strategy for exploiting such invariants through the construction of predictive mathematical models that incorporate them; and even Gauss’ strategy for controlling the inevitable inaccuracies in observation and (hence) errors in prediction by probabilistic modeling.
So the kind of science that INSITE success would entail is a social science based on an ongoing dialogue within different disciplines to better comprehend the richness and complexity of the world we aim to study, which departs in significant ways from the Galileo-Newton-Gauss tradition. The aim is to develop an approach that goes beyond the current innovation and sustainability literature and with a clear foundation in a complex systems perspective. These methods involve new interpretations of what theory is, and how theory can enter into productive, on-going dialogue with models and case studies.